• Journal of the Korean Applied Science and Technology
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• v.40 no.5
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• pp.1043-1054
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• 2023

Amidst the rapid growth of the vegan cosmetics market, consumer orientation towards environmental and ethical values has been intensifying. However, research on this subject remains limited. This study delves into the relationship between consumer value perception, environmental motivations, and perceived barriers influencing the purchase intentions of vegan cosmetics. Conducting a PLS-SEM analysis on a sample of 300 women with experience using vegan cosmetics, it was discerned that monetary value, social value, brand value, emotional value, quality value, and environmental knowledge play significant roles in influencing purchase intentions. The moderating effect analysis highlighted image barriers and value barriers as crucial factors. Through Importance-Performance Map Analysis, emotional value emerged as a pivotal element in strategizing to strengthen the purchasing intentions for vegan cosmetics. This research contributes both theoretically and practically to enhancing the competitive edge of the vegan cosmetics market and promoting sustainable consumption behavior.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.205-215
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• 2024

Manually mapping fractures in construction stone mines is challenging, time-consuming, and hazardous. In this method, there is no physical access to all points. In contrast, digital image processing offers a safe, cost-effective, and fast alternative, with the capability to map all joints. In this study, two methods of detecting the trace of discontinuities using image processing in construction stone mines are presented. To achieve this, we employ two modified Hough transform algorithms and the degree of neighborhood technique. Initially, we introduced a method for selecting the best edge detector and smoothing algorithms. Subsequently, the Canny detector and median smoother were identified as the most efficient tools. To trace discontinuities using the mentioned methods, common preprocessing steps were initially applied to the image. Following this, each of the two algorithms followed a distinct approach. The Hough transform algorithm was first applied to the image, and the traces were represented through line drawings. Subsequently, the Hough transform results were refined using fuzzy clustering and reduced clustering algorithms, along with a novel algorithm known as the farthest points' algorithm. Additionally, we developed another algorithm, the degree of neighborhood, tailored for detecting discontinuity traces in construction stones. After completing the common preprocessing steps, the thinning operation was performed on the target image, and the degree of neighborhood for lineament pixels was determined. Subsequently, short lines were removed, and the discontinuities were determined based on the degree of neighborhood. In the final step, we connected lines that were previously separated using the method to be described. The comparison of results demonstrates that image processing is a suitable tool for identifying rock mass discontinuity traces. Finally, a comparison of two images from different construction stone mines presented at the end of this study reveals that in images with fewer traces of discontinuities and a softer texture, both algorithms effectively detect the discontinuity traces.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.161-178
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• 2017

Whereas the demand for development of forested areas covering more than 60% of Korean territory, permission on the forest development has been still given from the perspective of effective land utilization rather than conservation. As the assessment of large forested areas usually focuses more on forest structure, it has its limitation of observing and analyzing the interior change in forest in this way. This study was aimed at computing landscape metrics using a presence vegetation map and FRAGTSTATS 4.2 and analyzing vegetation mosaics. Colonies in native vegetation were classified into a series of major groups and sub-groups based on the native species within the colonies. The colonies were investigated by analyzing a suite of landscape metrics - Core Area, Percentage of Landscape, Number of Patches, Patch Density, Largest Patch Index, Total Edge, Edge Density, Landscape Shape Index, Mean Patch Area, Euclidean Nearest Neighbor. In the Chungnam province major groups and sub-groups of colonies classified based on the proportion of pine and oak species, and pine species was the principal one in terms of distribution area. As for the competition between pines and oaks, while the coverage of pine-centered colonies were three times larger than those of oak-centered ones, pine colonies showed the greater number of patches and therefore higher fragmentation than oaks at the major group level. For the sub-groups, the largest coverage colonies were not only indicated by Pinus densiflora-Quesrcus mongolica colonies among P. densiflora-centered colonies, Q. accutissima colonies among Q. accutissima-centered ones, Q. accutissima-P. densiflora colonies among Q. accutissima-centered ones, Q. mongolica colonies among Q. mongolica-centered ones, P. thumbergii colonies among P. thumbergii-centered ones, and Q. serrata-Q. acutissima colonies among Q. serrata-centered ones, but also revealed more severely mosaicked than other smaller colonies. The overall mosaicking degree estimated by landscape metrics was considered useful for monitoring and investigating vegetation. However, in order to develop management strategy based on analyzing the reason for the mosaicking process and anticipating a trend in vegetation succession, it is essential to further study about ecological characteristics of each colony in the vegetation.

• Journal of the Korea Computer Graphics Society
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• v.16 no.1
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• pp.1-7
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• 2010

With the widespread use of vision-based surveillance systems, the capability for person identification is now an essential component. However, the CCTV cameras used in surveillance systems tend to produce relatively low-resolution images, making it difficult to use face recognition techniques for person identification. Therefore, an algorithm is proposed for person identification in CCTV camera images based on the clothing. Whenever a person is authenticated at the main entrance of a building, the clothing feature of that person is extracted and added to the database. Using a given image, the clothing area is detected using background subtraction and skin color detection techniques. The clothing feature vector is then composed of textural and color features of the clothing region, where the textural feature is extracted based on a local edge histogram, while the color feature is extracted using octree-based quantization of a color map. When given a query image, the person can then be identified by finding the most similar clothing feature from the database, where the Euclidean distance is used as the similarity measure. Experimental results show an 80% success rate for person identification with the proposed algorithm, and only a 43% success rate when using face recognition.

• Korean Journal of Environment and Ecology
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• v.30 no.3
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• pp.308-319
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• 2016

The purpose of this study is to identify distribution patterns of hydrophytes in the Mokpo wetland in relation to the depth of water. Sample surveys were conducted based on plant species distribution status and water depths at 274 spots. This study also developed a detailed depth distribution map for Mokpo wetland, which was never done in any previous studies. Through this study, it was found that the average depth of the wetland was 77cm (${\pm}29cm$) and the maximal depth was 157cm. The outer edge was no deeper than 60cm and the center approximately 120~130cm in depth, forming a concave bowl-like shape. This research confirmed inhabitation of 6 types of submerged plants (Verticillate hydrilla, Vallisneria natans, Najas graminea, Potamogeton cripus, Ceratophyllum demersum, and Potamogeton brechtoldi), and three types of floating leaved plants (Euryale ferox, Hydrocharis dubia and Trapa japonica) in the surveyed areas of the wetland. The distribution of these hydrophytes showed a statistically significant difference (${\chi}^2=982.2$, df = 8, p < 0.01), which confirms the fact that distribution varies based on environmental conditions. The most frequently observed species was Trapa japonicas at 244 times, and it showed a distribution pattern by which coverage increased with greater depth, as was also seen in the case of Potamogeton cripus. Five species-Euryale ferox, Hydrocharis dubid, Verticillate hydrilla, Najas graminea, and Ceratophyllum demersum-showed a negative correlation to depth, by which coverage decreased with increasing depth. It has been shown that fundamentally, the distribution of hydrophytes based on depth is affected by ecological factors, but also reflects the environmental properties of Mokpo wetland.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.505-513
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• 2014

The RapidEye can acquire the 6.5m spatial resolution satellite imagery with the high temporal resolution on each day, based on its constellation of five satellites. The image products are available in two processing levels of Basic 1B and Ortho 3A. The Basic 1B image have radiometric and sensor corrections and include RPCs (Rational Polynomial Coefficients) data. In Korea, the geometric accuracy of RapidEye imagery can be improved, based on the scaled national digital maps that had been built. In this paper, we present the fully automated procedures to georegister the 1B data using 1:25,000 digital maps. Those layers of map are selected if the layers appear well in the RapidEye image, and then the selected layers are RPCs-projected into the RapidEye 1B space for generating vector images. The automated edge-based matching between the vector image and RapidEye improves the accuracy of RPCs. The experimental results showed the accuracy improvement from 2.8 to 0.8 pixels in RMSE when compared to the maps.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.189-194
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• 2012

In this paper, we propose a query expansion method based on word graphs using pseudo-relevant and pseudo non-relevant documents to achieve performance improvement in information retrieval. The initially retrieved documents are classified into a core cluster when a document includes core query terms extracted by query term combinations and the degree of query term proximity. Otherwise, documents are classified into a non-core cluster. The documents that belong to a core query cluster can be seen as pseudo-relevant documents, and the documents that belong to a non-core cluster can be seen as pseudo non-relevant documents. Each cluster is represented as a graph which has nodes and edges. Each node represents a term and each edge represents proximity between the term and a query term. The term weight is calculated by subtracting the term weight in the non-core cluster graph from the term weight in the core cluster graph. It means that a term with a high weight in a non-core cluster graph should not be considered as an expanded term. Expansion terms are selected according to the term weights. Experimental results on TREC WT10g test collection show that the proposed method achieves 9.4% improvement over the language model in mean average precision.

• The KIPS Transactions:PartA
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• v.15A no.3
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• pp.141-149
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• 2008

In this research we present a novel method which combines and visualizes the design model and the FDM-based simulation result of solidification. Moreover we employ VR displays and visualize stereoscopic images to provide an effective analysis environment. First we reconstruct the solidification simulation result to a rectangular mesh model using a conventional simulation software. Then each point color of the reconstructed model represents a temperature value of its position. Next we map the two models by finding the nearest point of the reconstructed model for each point of the design model and then assign the point color of the design model as that of the reconstructed model. Before this mapping we apply mesh subdivision because the design model is composed of minimum number of points and that makes the point distribution of the design model not uniform compared with the reconstructed model. In this process the original shape is preserved in the manner that points are added to the mesh edge which length is longer than a predefined threshold value. The implemented system visualizes the solidification simulation data on the design model, which allows the user to understand the object geometry precisely. The immersive and realistic working environment constructed with use of VR display can support the user to discover the defect occurrence faster and more effectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.12
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• pp.6986-6992
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• 2014

The generalized Voronoi graph (GVG) is a topological map of a constrained environment. This is defined in terms of workspace distance measurements using only sensor-provided information, with a robot having a maximum distance from obstacles, and is the optimum for exploration and obstacle avoidance. This is the safest path for the robot, and is very significant when studying the GVG edges of highly articulated robots. In previous work, the point-GVG edge and Rod-GVG were built with point robot and rod robot using sensor-based control. An attempt was made to use a higher degree of freedom robot to build GVG edges. This paper presents GVG-based a new local roadmap for the two-link robot in the constrained two-dimensional environment. This new local roadmap is called the two-identical-link generalized Voronoi graph (L2-GVG). This is used to explore an unknown planar workspace and build a local roadmap in an unknown configuration space $R^2{\times}T^2$ for a planar two-identical-link robot. The two-identical-link GVG also can be constructed using only sensor-provided information. These results show the more complex properties of two-link-GVG, which are very different from point-GVG and rod-GVG. Furthermore, this approach draws on the experience of other highly articulated robots.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.2
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• pp.1-9
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• 2008

In this paper, to extract object regions in stereo image, we propose an enhanced algorithm that extracts objects combining both of brightness information and disparity information. The approach that extracts objects using both has been studied by Ping and Chaohui. In their algorithm, the segmentation for an input image is carried out using the brightness, and integration of segmented regions in consideration of disparity information within the previously segmented regions. In the regions where the brightness values between object regions and background regions are similar, however, the segmented regions probably include both of object regions and background regions. It may cause incorrect object extraction in the merging process executed in the unit of the segmented region. To solve this problem, in proposed method, we adopt the merging process which is performed in pixel unit. In addition, we perform the bi-directional stereo matching process to enhance reliability of the disparity information and supplement the disparity information resulted from a single directional matching process. Further searching for disparity is decided by edge information of the input image. The proposed method gives good performance in the object extraction since we find the disparity information that is not extracted in the traditional methods. Finally, we evaluate our method by experiments for the pictures acquired from a real stereoscopic camera.